The emotional interaction from the perspective of human-machine communication: The case study of intelligent home products

This study uses a mixed-methods approach that combines factor analysis with expert interviews to explore the key factors shaping human-machine interaction in intelligent home environments, particularly within the emerging metaverse context. Fifteen significant factors were identified and classified into two categories: design-optimizable factors such as emotional engagement, adaptability, and usability, and user-centric factors like personality traits, behavioral habits, and regulatory constraints. Emotional and feeling-oriented elements, including trust, fun, and surprise, emerged slightly more influential than efficiency-driven factors like information accuracy and systematization. Expert insights highlighted the critical role of social influences, such as peer endorsement and interaction atmosphere, especially in enhancing emotional acceptance among children. The novelty of this study lies in its integration of metaverse-driven scenarios and visual interaction mapping to analyze both positive and negative drivers of user engagement across physical, virtual, and hybrid spaces. Based on these findings, the study recommends a development path of "entity-based, hybrid-led, virtual-supplemented" design supported by AR and environmental sensing technologies, alongside emotionally resonant features and greater user control over data and system intelligence to enhance privacy, satisfaction, and overall emotional comfort in smart home interactions.